ArticleExperimental brain research2023
Comparing anticipatory and stop-signal response inhibition with a novel, open-source selective stopping toolbox.
Article in Experimental brain research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- When Stopping Requires Going: Physiological Similarities Between Action Cancellation and the Cancellation of Action Cancellation.The European journal of neuroscience · 2025Article
- Article
- The limits of action control for deceptive actions in sports: Response inhibition for the basketball pump fake.PloS one · 2025Article
- Action inhibition in a sport-specific paradigm: examining the limits of action control in basketball.Psychological research · 2024Article
- A global pause generates nonselective response inhibition during selective stopping.Cerebral cortex (New York, N.Y. : 1991) · 2023Article
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Authors and funding
4 authors.
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Abstract
Response inhibition is essential for terminating inappropriate actions and, in some cases, may be required selectively. Selective stopping can be investigated with multicomponent anticipatory or stop-signal response inhibition paradigms. Here we provide a freely available open-source Selective Stopping Toolbox (SeleST) to investigate selective stopping using either anticipatory or stop-signal task variants. This study aimed to evaluate selective stopping between the anticipatory and stop-signal variants using SeleST and provide guidance to researchers for future use. Forty healthy human participants performed bimanual anticipatory response inhibition and stop-signal tasks in SeleST. Responses were more variable and slowed to a greater extent during the stop-signal than in the anticipatory paradigm. However, the stop-signal paradigm better conformed to the assumption of the independent race model of response inhibition. The expected response delay during selective stop trials was present in both variants. These findings indicate that selective stopping can successfully be investigated with either anticipatory or stop-signal paradigms in SeleST. We propose that the anticipatory paradigm should be used when strict control of response times is desired, while the stop-signal paradigm should be used when it is desired to estimate stop-signal reaction time with the independent race model. Importantly, the dual functionality of SeleST allows researchers flexibility in paradigm selection when investigating selective stopping.
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